{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": null,
   "metadata": {},
   "outputs": [],
   "source": [
    "# Execute this cell to install dependencies\n",
    "%pip install sf-hamilton[visualization]"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Dagster comparison [![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/dagworks-inc/hamilton/blob/main/examples/dagster/hamilton_code/notebook.ipynb) [![GitHub badge](https://img.shields.io/badge/github-view_source-2b3137?logo=github)](https://github.com/apache/hamilton/blob/main/examples/dagster/hamilton_code/notebook.ipynb)\n",
    "\n",
    "\n",
    "This notebook shows how you can use Hamilton in a notebook for interactive development. The code is similar to the content of `run.py`.\n",
    "\n",
    "[Tips on Hamilton + notebooks in the docs](https://hamilton.apache.org/how-tos/use-in-jupyter-notebook/)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Imports"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from IPython.display import display\n",
    "from hamilton import driver\n",
    "from hamilton.io.materialization import to\n",
    "from hamilton.plugins import matplotlib_extensions \n",
    "from mock_api import DataGeneratorResource\n",
    "\n",
    "import dataflow  # dataflow definition"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Create Driver"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
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       "<title>%3</title>\n",
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       "<g id=\"clust1\" class=\"cluster\">\n",
       "<title>cluster__legend</title>\n",
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       "<text text-anchor=\"middle\" x=\"156\" y=\"-303.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">Legend</text>\n",
       "</g>\n",
       "<!-- topstories -->\n",
       "<g id=\"node1\" class=\"node\">\n",
       "<title>topstories</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M592.5,-64C592.5,-64 513.5,-64 513.5,-64 507.5,-64 501.5,-58 501.5,-52 501.5,-52 501.5,-12 501.5,-12 501.5,-6 507.5,0 513.5,0 513.5,0 592.5,0 592.5,0 598.5,0 604.5,-6 604.5,-12 604.5,-12 604.5,-52 604.5,-52 604.5,-58 598.5,-64 592.5,-64\"/>\n",
       "<text text-anchor=\"start\" x=\"512.5\" y=\"-42.8\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">topstories</text>\n",
       "<text text-anchor=\"start\" x=\"514.5\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">DataFrame</text>\n",
       "</g>\n",
       "<!-- title -->\n",
       "<g id=\"node4\" class=\"node\">\n",
       "<title>title</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M737,-64C737,-64 696,-64 696,-64 690,-64 684,-58 684,-52 684,-52 684,-12 684,-12 684,-6 690,0 696,0 696,0 737,0 737,0 743,0 749,-6 749,-12 749,-12 749,-52 749,-52 749,-58 743,-64 737,-64\"/>\n",
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       "</g>\n",
       "<!-- topstories&#45;&gt;title -->\n",
       "<g id=\"edge4\" class=\"edge\">\n",
       "<title>topstories&#45;&gt;title</title>\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"673.8,-35.5 683.8,-32 673.8,-28.5 673.8,-35.5\"/>\n",
       "</g>\n",
       "<!-- signups -->\n",
       "<g id=\"node2\" class=\"node\">\n",
       "<title>signups</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M438,-187C438,-187 363,-187 363,-187 357,-187 351,-181 351,-175 351,-175 351,-135 351,-135 351,-129 357,-123 363,-123 363,-123 438,-123 438,-123 444,-123 450,-129 450,-135 450,-135 450,-175 450,-175 450,-181 444,-187 438,-187\"/>\n",
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       "<text text-anchor=\"start\" x=\"362\" y=\"-137.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">DataFrame</text>\n",
       "</g>\n",
       "<!-- registered_at -->\n",
       "<g id=\"node6\" class=\"node\">\n",
       "<title>registered_at</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M605,-187C605,-187 501,-187 501,-187 495,-187 489,-181 489,-175 489,-175 489,-135 489,-135 489,-129 495,-123 501,-123 501,-123 605,-123 605,-123 611,-123 617,-129 617,-135 617,-135 617,-175 617,-175 617,-181 611,-187 605,-187\"/>\n",
       "<text text-anchor=\"start\" x=\"500\" y=\"-165.8\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">registered_at</text>\n",
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       "</g>\n",
       "<!-- signups&#45;&gt;registered_at -->\n",
       "<g id=\"edge6\" class=\"edge\">\n",
       "<title>signups&#45;&gt;registered_at</title>\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"478.84,-158.5 488.84,-155 478.84,-151.5 478.84,-158.5\"/>\n",
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       "<!-- most_frequent_words -->\n",
       "<g id=\"node3\" class=\"node\">\n",
       "<title>most_frequent_words</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M995,-64C995,-64 828,-64 828,-64 822,-64 816,-58 816,-52 816,-52 816,-12 816,-12 816,-6 822,0 828,0 828,0 995,0 995,0 1001,0 1007,-6 1007,-12 1007,-12 1007,-52 1007,-52 1007,-58 1001,-64 995,-64\"/>\n",
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       "<text text-anchor=\"start\" x=\"898.5\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">dict</text>\n",
       "</g>\n",
       "<!-- top_25_words_plot -->\n",
       "<g id=\"node7\" class=\"node\">\n",
       "<title>top_25_words_plot</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M1191,-64C1191,-64 1048,-64 1048,-64 1042,-64 1036,-58 1036,-52 1036,-52 1036,-12 1036,-12 1036,-6 1042,0 1048,0 1048,0 1191,0 1191,0 1197,0 1203,-6 1203,-12 1203,-12 1203,-52 1203,-52 1203,-58 1197,-64 1191,-64\"/>\n",
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       "</g>\n",
       "<!-- most_frequent_words&#45;&gt;top_25_words_plot -->\n",
       "<g id=\"edge7\" class=\"edge\">\n",
       "<title>most_frequent_words&#45;&gt;top_25_words_plot</title>\n",
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       "</g>\n",
       "<!-- title&#45;&gt;most_frequent_words -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>title&#45;&gt;most_frequent_words</title>\n",
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       "<!-- topstory_ids -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>topstory_ids</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M448,-64C448,-64 353,-64 353,-64 347,-64 341,-58 341,-52 341,-52 341,-12 341,-12 341,-6 347,0 353,0 353,0 448,0 448,0 454,0 460,-6 460,-12 460,-12 460,-52 460,-52 460,-58 454,-64 448,-64\"/>\n",
       "<text text-anchor=\"start\" x=\"352\" y=\"-42.8\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">topstory_ids</text>\n",
       "<text text-anchor=\"start\" x=\"390\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">list</text>\n",
       "</g>\n",
       "<!-- topstory_ids&#45;&gt;topstories -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>topstory_ids&#45;&gt;topstories</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M460.12,-32C470.27,-32 480.85,-32 491.06,-32\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"491.12,-35.5 501.12,-32 491.12,-28.5 491.12,-35.5\"/>\n",
       "</g>\n",
       "<!-- latest_signup -->\n",
       "<g id=\"node8\" class=\"node\">\n",
       "<title>latest_signup</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M768,-228C768,-228 665,-228 665,-228 659,-228 653,-222 653,-216 653,-216 653,-176 653,-176 653,-170 659,-164 665,-164 665,-164 768,-164 768,-164 774,-164 780,-170 780,-176 780,-176 780,-216 780,-216 780,-222 774,-228 768,-228\"/>\n",
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       "<!-- registered_at&#45;&gt;latest_signup -->\n",
       "<g id=\"edge8\" class=\"edge\">\n",
       "<title>registered_at&#45;&gt;latest_signup</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M617.37,-171.09C625.75,-173.22 634.4,-175.41 642.92,-177.57\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"642.29,-181.03 652.85,-180.09 644.02,-174.24 642.29,-181.03\"/>\n",
       "</g>\n",
       "<!-- earliest_signup -->\n",
       "<g id=\"node9\" class=\"node\">\n",
       "<title>earliest_signup</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M775,-146C775,-146 658,-146 658,-146 652,-146 646,-140 646,-134 646,-134 646,-94 646,-94 646,-88 652,-82 658,-82 658,-82 775,-82 775,-82 781,-82 787,-88 787,-94 787,-94 787,-134 787,-134 787,-140 781,-146 775,-146\"/>\n",
       "<text text-anchor=\"start\" x=\"657\" y=\"-124.8\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">earliest_signup</text>\n",
       "<text text-anchor=\"start\" x=\"707\" y=\"-96.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">int</text>\n",
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       "<!-- registered_at&#45;&gt;earliest_signup -->\n",
       "<g id=\"edge9\" class=\"edge\">\n",
       "<title>registered_at&#45;&gt;earliest_signup</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M617.37,-138.91C623.51,-137.35 629.8,-135.76 636.08,-134.16\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"637.08,-137.52 645.91,-131.67 635.36,-130.73 637.08,-137.52\"/>\n",
       "</g>\n",
       "<!-- _signups_inputs -->\n",
       "<g id=\"node10\" class=\"node\">\n",
       "<title>_signups_inputs</title>\n",
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       "<text text-anchor=\"start\" x=\"15\" y=\"-150.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">hackernews_api</text>\n",
       "<text text-anchor=\"start\" x=\"131\" y=\"-150.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">DataGeneratorResource</text>\n",
       "</g>\n",
       "<!-- _signups_inputs&#45;&gt;signups -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>_signups_inputs&#45;&gt;signups</title>\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"340.71,-158.5 350.71,-155 340.71,-151.5 340.71,-158.5\"/>\n",
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       "<!-- _topstory_ids_inputs -->\n",
       "<g id=\"node11\" class=\"node\">\n",
       "<title>_topstory_ids_inputs</title>\n",
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       "<text text-anchor=\"start\" x=\"93\" y=\"-27.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">newstories_url</text>\n",
       "<text text-anchor=\"start\" x=\"200\" y=\"-27.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">str</text>\n",
       "</g>\n",
       "<!-- _topstory_ids_inputs&#45;&gt;topstory_ids -->\n",
       "<g id=\"edge5\" class=\"edge\">\n",
       "<title>_topstory_ids_inputs&#45;&gt;topstory_ids</title>\n",
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       "<!-- input -->\n",
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       "<title>input</title>\n",
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       "</g>\n",
       "<!-- function -->\n",
       "<g id=\"node13\" class=\"node\">\n",
       "<title>function</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M184,-232.5C184,-232.5 128,-232.5 128,-232.5 122,-232.5 116,-226.5 116,-220.5 116,-220.5 116,-207.5 116,-207.5 116,-201.5 122,-195.5 128,-195.5 128,-195.5 184,-195.5 184,-195.5 190,-195.5 196,-201.5 196,-207.5 196,-207.5 196,-220.5 196,-220.5 196,-226.5 190,-232.5 184,-232.5\"/>\n",
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       "</g>\n",
       "</svg>\n"
      ],
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       "<graphviz.graphs.Digraph at 0x7f667c9b9570>"
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     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "dr = driver.Builder().with_modules(dataflow).build()\n",
    "dr.display_all_functions()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Define inputs and requested nodes\n",
    "\n",
    "Note that we use a list of node names to query and the `Driver.execute()` method instead of defining materializers for `Driver.materialize()`"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
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       "<title>title</title>\n",
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       "<title>topstories&#45;&gt;title</title>\n",
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       "<text text-anchor=\"start\" x=\"649.5\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">dict</text>\n",
       "</g>\n",
       "<!-- top_25_words_plot -->\n",
       "<g id=\"node6\" class=\"node\">\n",
       "<title>top_25_words_plot</title>\n",
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       "<text text-anchor=\"start\" x=\"848\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">Figure</text>\n",
       "</g>\n",
       "<!-- most_frequent_words&#45;&gt;top_25_words_plot -->\n",
       "<g id=\"edge5\" class=\"edge\">\n",
       "<title>most_frequent_words&#45;&gt;top_25_words_plot</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M758.06,-32C764.23,-32 770.43,-32 776.59,-32\"/>\n",
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       "</g>\n",
       "<!-- title&#45;&gt;most_frequent_words -->\n",
       "<g id=\"edge3\" class=\"edge\">\n",
       "<title>title&#45;&gt;most_frequent_words</title>\n",
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       "<polygon fill=\"black\" stroke=\"black\" points=\"556.77,-35.5 566.77,-32 556.77,-28.5 556.77,-35.5\"/>\n",
       "</g>\n",
       "<!-- topstory_ids -->\n",
       "<g id=\"node5\" class=\"node\">\n",
       "<title>topstory_ids</title>\n",
       "<path fill=\"#ffc857\" stroke=\"black\" d=\"M203.5,-64C203.5,-64 108.5,-64 108.5,-64 102.5,-64 96.5,-58 96.5,-52 96.5,-52 96.5,-12 96.5,-12 96.5,-6 102.5,0 108.5,0 108.5,0 203.5,0 203.5,0 209.5,0 215.5,-6 215.5,-12 215.5,-12 215.5,-52 215.5,-52 215.5,-58 209.5,-64 203.5,-64\"/>\n",
       "<text text-anchor=\"start\" x=\"107.5\" y=\"-42.8\" font-family=\"Helvetica,sans-Serif\" font-weight=\"bold\" font-size=\"14.00\">topstory_ids</text>\n",
       "<text text-anchor=\"start\" x=\"145.5\" y=\"-14.8\" font-family=\"Helvetica,sans-Serif\" font-style=\"italic\" font-size=\"14.00\">list</text>\n",
       "</g>\n",
       "<!-- topstory_ids&#45;&gt;topstories -->\n",
       "<g id=\"edge1\" class=\"edge\">\n",
       "<title>topstory_ids&#45;&gt;topstories</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M215.57,-32C250.64,-32 295.14,-32 330.61,-32\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"330.83,-35.5 340.83,-32 330.83,-28.5 330.83,-35.5\"/>\n",
       "</g>\n",
       "<!-- _signups_inputs -->\n",
       "<g id=\"node7\" class=\"node\">\n",
       "<title>_signups_inputs</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"black\" stroke-dasharray=\"5,2\" points=\"312,-136.5 0,-136.5 0,-91.5 312,-91.5 312,-136.5\"/>\n",
       "<text text-anchor=\"start\" x=\"15\" y=\"-109.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">hackernews_api</text>\n",
       "<text text-anchor=\"start\" x=\"131\" y=\"-109.8\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">DataGeneratorResource</text>\n",
       "</g>\n",
       "<!-- _signups_inputs&#45;&gt;signups -->\n",
       "<g id=\"edge2\" class=\"edge\">\n",
       "<title>_signups_inputs&#45;&gt;signups</title>\n",
       "<path fill=\"none\" stroke=\"black\" d=\"M312.11,-114C319.26,-114 326.21,-114 332.82,-114\"/>\n",
       "<polygon fill=\"black\" stroke=\"black\" points=\"332.91,-117.5 342.91,-114 332.91,-110.5 332.91,-117.5\"/>\n",
       "</g>\n",
       "<!-- input -->\n",
       "<g id=\"node8\" class=\"node\">\n",
       "<title>input</title>\n",
       "<polygon fill=\"#ffffff\" stroke=\"black\" stroke-dasharray=\"5,2\" points=\"185.5,-301.5 126.5,-301.5 126.5,-264.5 185.5,-264.5 185.5,-301.5\"/>\n",
       "<text text-anchor=\"middle\" x=\"156\" y=\"-279.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">input</text>\n",
       "</g>\n",
       "<!-- function -->\n",
       "<g id=\"node9\" class=\"node\">\n",
       "<title>function</title>\n",
       "<path fill=\"#b4d8e4\" stroke=\"black\" d=\"M184,-246.5C184,-246.5 128,-246.5 128,-246.5 122,-246.5 116,-240.5 116,-234.5 116,-234.5 116,-221.5 116,-221.5 116,-215.5 122,-209.5 128,-209.5 128,-209.5 184,-209.5 184,-209.5 190,-209.5 196,-215.5 196,-221.5 196,-221.5 196,-234.5 196,-234.5 196,-240.5 190,-246.5 184,-246.5\"/>\n",
       "<text text-anchor=\"middle\" x=\"156\" y=\"-224.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">function</text>\n",
       "</g>\n",
       "<!-- output -->\n",
       "<g id=\"node10\" class=\"node\">\n",
       "<title>output</title>\n",
       "<path fill=\"#ffc857\" stroke=\"black\" d=\"M178,-191.5C178,-191.5 134,-191.5 134,-191.5 128,-191.5 122,-185.5 122,-179.5 122,-179.5 122,-166.5 122,-166.5 122,-160.5 128,-154.5 134,-154.5 134,-154.5 178,-154.5 178,-154.5 184,-154.5 190,-160.5 190,-166.5 190,-166.5 190,-179.5 190,-179.5 190,-185.5 184,-191.5 178,-191.5\"/>\n",
       "<text text-anchor=\"middle\" x=\"156\" y=\"-169.3\" font-family=\"Helvetica,sans-Serif\" font-size=\"14.00\">output</text>\n",
       "</g>\n",
       "</g>\n",
       "</svg>\n"
      ],
      "text/plain": [
       "<graphviz.graphs.Digraph at 0x7f667c8343d0>"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "inputs = dict(\n",
    "    hackernews_api=DataGeneratorResource(num_days=30),\n",
    ")\n",
    "\n",
    "requested_nodes = [\n",
    "    \"topstory_ids\",\n",
    "    \"most_frequent_words\",\n",
    "    \"topstories\",\n",
    "    \"signups\",\n",
    "    \"top_25_words_plot\",\n",
    "]\n",
    "\n",
    "dr.visualize_execution(requested_nodes, inputs=inputs)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Execute"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['topstory_ids', 'most_frequent_words', 'topstories', 'signups', 'top_25_words_plot'])"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
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       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>by</th>\n",
       "      <th>descendants</th>\n",
       "      <th>id</th>\n",
       "      <th>kids</th>\n",
       "      <th>score</th>\n",
       "      <th>time</th>\n",
       "      <th>title</th>\n",
       "      <th>type</th>\n",
       "      <th>url</th>\n",
       "      <th>text</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>rbanffy</td>\n",
       "      <td>9.0</td>\n",
       "      <td>39793044</td>\n",
       "      <td>[39793204, 39793227, 39793158, 39793184]</td>\n",
       "      <td>38</td>\n",
       "      <td>1711129553</td>\n",
       "      <td>Boom Announces Successful Flight of XB-1 Demon...</td>\n",
       "      <td>story</td>\n",
       "      <td>https://boomsupersonic.com/flyby/inaugural-fir...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>samuelbrashears</td>\n",
       "      <td>42.0</td>\n",
       "      <td>39792136</td>\n",
       "      <td>[39792782, 39792830, 39793117, 39792455, 39792...</td>\n",
       "      <td>55</td>\n",
       "      <td>1711124153</td>\n",
       "      <td>Launch HN: DryMerge (YC W24) – Automate Workfl...</td>\n",
       "      <td>story</td>\n",
       "      <td>NaN</td>\n",
       "      <td>Hi HN! We&amp;#x27;re Edward and Sam, the founders...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>kvptkr</td>\n",
       "      <td>4.0</td>\n",
       "      <td>39791301</td>\n",
       "      <td>[39793213, 39792211, 39793207]</td>\n",
       "      <td>32</td>\n",
       "      <td>1711119126</td>\n",
       "      <td>Show HN: Leaping – Debug Python tests instantl...</td>\n",
       "      <td>story</td>\n",
       "      <td>https://github.com/leapingio/leaping</td>\n",
       "      <td>Hi HN! We’re Adrien and Kanav. We met at our p...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>ubutler</td>\n",
       "      <td>62.0</td>\n",
       "      <td>39788322</td>\n",
       "      <td>[39788517, 39788951, 39792921, 39791935, 39791...</td>\n",
       "      <td>284</td>\n",
       "      <td>1711094018</td>\n",
       "      <td>Show HN: Mapping almost every law, regulation ...</td>\n",
       "      <td>story</td>\n",
       "      <td>https://umarbutler.com/mapping-almost-every-la...</td>\n",
       "      <td>Hey HN,&lt;p&gt;After months of hard work, I am exci...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>Brajeshwar</td>\n",
       "      <td>45.0</td>\n",
       "      <td>39792383</td>\n",
       "      <td>[39792852, 39792593, 39792528, 39793071, 39792...</td>\n",
       "      <td>76</td>\n",
       "      <td>1711125603</td>\n",
       "      <td>2K earthquakes in 1 day off Canada coast</td>\n",
       "      <td>story</td>\n",
       "      <td>https://www.livescience.com/planet-earth/earth...</td>\n",
       "      <td>NaN</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                by  descendants        id  \\\n",
       "0          rbanffy          9.0  39793044   \n",
       "1  samuelbrashears         42.0  39792136   \n",
       "2           kvptkr          4.0  39791301   \n",
       "3          ubutler         62.0  39788322   \n",
       "4       Brajeshwar         45.0  39792383   \n",
       "\n",
       "                                                kids  score        time  \\\n",
       "0           [39793204, 39793227, 39793158, 39793184]     38  1711129553   \n",
       "1  [39792782, 39792830, 39793117, 39792455, 39792...     55  1711124153   \n",
       "2                     [39793213, 39792211, 39793207]     32  1711119126   \n",
       "3  [39788517, 39788951, 39792921, 39791935, 39791...    284  1711094018   \n",
       "4  [39792852, 39792593, 39792528, 39793071, 39792...     76  1711125603   \n",
       "\n",
       "                                               title   type  \\\n",
       "0  Boom Announces Successful Flight of XB-1 Demon...  story   \n",
       "1  Launch HN: DryMerge (YC W24) – Automate Workfl...  story   \n",
       "2  Show HN: Leaping – Debug Python tests instantl...  story   \n",
       "3  Show HN: Mapping almost every law, regulation ...  story   \n",
       "4           2K earthquakes in 1 day off Canada coast  story   \n",
       "\n",
       "                                                 url  \\\n",
       "0  https://boomsupersonic.com/flyby/inaugural-fir...   \n",
       "1                                                NaN   \n",
       "2               https://github.com/leapingio/leaping   \n",
       "3  https://umarbutler.com/mapping-almost-every-la...   \n",
       "4  https://www.livescience.com/planet-earth/earth...   \n",
       "\n",
       "                                                text  \n",
       "0                                                NaN  \n",
       "1  Hi HN! We&#x27;re Edward and Sam, the founders...  \n",
       "2  Hi HN! We’re Adrien and Kanav. We met at our p...  \n",
       "3  Hey HN,<p>After months of hard work, I am exci...  \n",
       "4                                                NaN  "
      ]
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    },
    {
     "data": {
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",
      "text/plain": [
       "<Figure size 1000x600 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "results = dr.execute(requested_nodes, inputs=inputs)\n",
    "\n",
    "display(\n",
    "    results.keys(),\n",
    "    results[\"top_25_words_plot\"],\n",
    "    results[\"topstories\"].head(),\n",
    ")"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "venv",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.10.9"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 2
}
